Sailing on Encrypted Seas: The Archive and Digital Memory in African and Diasporic Futurism
Bibliographic record
Abstract
Digitization has commonly been marketed as a predictive technology that can enable humanity to intercede into the future. This faith in digital media's prophetic powers, however, obfuscates the fact that digitization is unavoidably stuck in the past. In effect, digitization transforms the past into highly mutable and volatile data sets that are persistently rewritten by computer's memory refresh circuits. While some lament this temporal incongruity as problematic to the archival process, African and diasporic futurist artists are utilizing digital distortion as an opportunity to emplace the archival process within the sea and reimagine the archive as an impermanent, transitory, and fluid practice that has the capacity to usher in a more culturally and scientifically nuanced understanding of memory. This article explores the capacity of the sea to reorientate digital humanities scholarship around the cyclical interplay between machinic, environmental, and human social systems and craft historiographical methods around envisioning a viable future for humanity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.011 | 0.025 |
| Scholarly communication | 0.010 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".